Data Engineer — Finance (Train AI Models Part Time!)

Skip to main content Data Engineer — Finance (Train AI Models Part Time!) hackajob United States Data Engineer — Finance (Train AI Models Part Time!) hackajob United States 1 week ago Be among the first 25 applicants See who hackajob has hired for this role Report this job Use AI to assess how you fit Get AI-powered advice on this job and more exclusive features. Am I a good fit for this job? Tailor my resume Sign in to access AI-powered advices Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. Sign in to evaluate your skills Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. Sign in to tailor your resume Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. hackajob is collaborating with Mercor to connect them with exceptional professionals for this role.Onsite: San Francisco, CA / New York, NY / Bellevue, WA** A fast-growing AI company's Finance org is hiring a Data Engineer to build the data infrastructure its CFO team runs on. You'll join a small, fast-moving team with a broad mandate: build the pipelines, fix what's broken, and do whatever it takes to keep Finance's roadmap moving. This is a 6-month, full-time onsite contract, with room to extend based on performance and business need. ## Responsibilities - Build and maintain PySpark-based data pipelines that keep Finance's data flowing accurately and on time. - Write and optimize SQL to pull, join, and validate large volumes of financial data. - Partner with Finance and engineering stakeholders to turn ambiguous asks into working data infrastructure. - Track down and fix pipeline issues quickly, owning data quality end to end. ## Qualifications - 2–4 years of experience as a Data Engineer. - Hands-on experience with PySpark and large-scale/distributed data processing. - Strong SQL skills — you'll be tested on this directly across two technical screens. - Comfortable working onsite full-time. - Bachelor's degree in Computer Science or a related field. - Strong written...